Journal of Artificial Intelligence and Data Science 2791-8335 Izmir Katip Celebi University Artificial Intelligence Yapay Zeka Development of Android-based Internet of Things Application for Data Tracking in Smart Marble Factories Gurkan Caglar IZMIR KATIP CELEBI UNIVERSITY 08 30 2021 1 1 41 44 06 28 2021 08 19 2021 Copyright © 2021, Journal of Artificial Intelligence and Data Science 2021 Journal of Artificial Intelligence and Data Science

Internet of Things is one of the most important technological components of Industry 4.0. Internet of Things technology has become an even more critical research subject by using it with cloud computing technology that is constantly evolving. In this study, it is aimed to contribute to digital transformation in the marble factories. Therefore, an Android-based Internet of Things application has been developed for data tracking during the drying stage of the marble. NodeMCU, DHT11 temperature and humidity sensor, Firebase RealTime Database have been used to build the data tracking system. This system has been supported by the Android-based mobile application created in the Android Studio Integrated Development Environment using Java programming language. As a result, losses during the production stage can be minimized by ensuring data tracking during the marble's drying phase.

 Android industry 4.0 internet of things IoT marble drying system smart factory Izmir Katip Celebi University of Scientific Research Projects Coordinatorship 2021-TYL-FEBE-0009 [1] K. Çelik, S. Güleryüz, and H. Özköse, “4. Endüstri Devrimine Kuramsal Bakış,” Avrasya Sos. ve Ekon. Araştırmaları Derg., vol. 5, no. 9, pp. 86–95, 2018. [2] M. A. K. Bahrin, M. F. Othman, N. H. N. Azli, and M. F. Talib, “Industry 4.0: a review on industrial automation and robotic,” Jurnal Teknologi, vol. 78, no. 6–13. Penerbit UTM Press, pp. 137–143, Jun. 28, 2016, doi: 10.11113/jt.v78.9285. [3] N. S. Pamuk and M. Soysal, “Yeni Sanayi Devrimi Üzerine Bir İnceleme,” Veriml. Derg., no. 1, pp. 41–66, 2018. [4] M. Hanefi Calp, E. Bahçekapılı, and M. Berigel, “Endüstri 4.0 Kapsamında Akıllı Fabrikaların İncelenmesi,” IMISC, Jan. 2019. doi: 10.6084/M9.FIGSHARE.7564886.V1. [5] D. Zhang, J. Wan, C. H. Hsu, and A. Rayes, “Industrial technologies and applications for the Internet of Things,” Computer Networks, vol. 101. pp. 1–4, 2016, doi: 10.1016/j.comnet.2016.02.019. [6] Z. Shu, J. Wan, D. Zhang, and D. Li, “Cloud-Integrated Cyber-Physical Systems for Complex Industrial Applications,” Mob. Networks Appl., vol. 21, no. 5, pp. 865–878, 2016, doi: 10.1007/s11036-015-0664-6. [7] F. Terroso-Saenz, A. González-Vidal, A. P. Ramallo-González, and A. F. Skarmeta, “An open IoT platform for the management and analysis of energy data,” Futur. Gener. Comput. Syst., vol. 92, pp. 1066–1079, 2019, doi: 10.1016/j.future.2017.08.046. [8] A. Rashed et al., “Integrated IoT medical platform for remote healthcare and assisted living,” in 2017 Proceedings of the JapanAfrica Conference on Electronics, Communications, and Computers, JAC-ECC 2017, 2018, vol. 2018-Janua, pp. 160–163, doi: 10.1109/JEC-ECC.2017.8305801. [9] M. Taştan, “Nesnelerin İnterneti Tabanlı Akıllı Sulama ve Uzaktan İzleme Sistemi,” Eur. J. Sci. Technol., pp. 229–236, 2019, doi: 10.31590/ejosat.525149. [10] M. Kumar, V. M. Shenbagaraman, R. N. Shaw, and A. Ghosh, “Predictive data analysis for energy management of a smart factory leading to sustainability,” in Lecture Notes in Electrical Engineering, 2021, vol. 661, pp. 765–773, doi: 10.1007/978-981-15-4692- 1_58. [11] S. Hamilton, “Real-Time Big Data Analytics, Sustainable Industry 4.0 Wireless Networks, and Internet of Things-based Decision Support Systems in Cyber-Physical Smart Manufacturing,” Econ. Manag. Financ. Mark., vol. 16, no. 2, pp. 84-94, 2021, doi: 10.22381/emfm16220215. [12] “NodeMcu DHT11 & MQTT « osoyoo.com.” https://osoyoo.com/2018/01/17/nodemcu-dht11-mqtt/ (accessed Jun. 15, 2021)